-------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\Siyao\Dropbox\Yue-Siyao\Project Subsidy\PSRM replication files\analysis_main.log
  log type:  text
 opened on:  18 Aug 2022, 21:35:11

. 
. ***
. *Directory 
. ***
. *cd to directory of choice 
. use "subsidy_leader.dta"

. 
. *** 
. *Analysis 
. ***
. xtset firmID year  
       panel variable:  firmID (unbalanced)
        time variable:  year, 2008 to 2015, but with a gap
                delta:  1 unit

. 
. *set up fe
. egen industry_name_CSRC_f=group(industry_name_CSRC)

. egen industry_year=group(industry_name_CSRC year)

. encode current_gvn, gen(current_gvn_f)

. encode current_psec, gen(current_psec_f)

. encode mayor, gen(mayor_f)

. encode msec, gen(msec_f)

. 
. count //1951
  1,951

. 
. *Table 1: Descriptive statistics
. gen subsidy_assets_number= subsidy_assets/100 //the original measure includes only the pe
> rcentage number
(346 missing values generated)

. eststo clear

. estpost summarize subsidy TotalAssets subsidy_assets_number revenue ROA if subsidy!=. & p
> rivate!=. 

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max) 
-------------+-----------------------------------------------------------------------------
     subsidy |      1516       1516   3085.068   1.03e+08   10169.68          0   161179.6 
 TotalAssets |      1516       1516    2676939   7.72e+13    8785258    1068.88   1.07e+08 
subsidy_as~r |      1516       1516   .0028513   .0000766   .0087543          0   .2526009 
     revenue |      1515       1515   880659.3   4.69e+12    2165656   2027.811   1.04e+07 
         ROA |      1516       1516    6.45962   109.6453   10.47117   -135.286   165.1254 

             |    e(sum) 
-------------+-----------
     subsidy |   4676964 
 TotalAssets |  4.06e+09 
subsidy_as~r |  4.322499 
     revenue |  1.33e+09 
         ROA |  9792.784 

. esttab using Table1a.tex, replace ///
>     cells("count(fmt(0)) mean(fmt(2)) sd(fmt(2)) min(fmt(2)) max(fmt(2))") ///
>     title("Descriptive Statistics") nomtitle nonumber noobs 
(note: file Table1a.tex not found)
(output written to Table1a.tex)

. tabstat subsidy_assets_number if subsidy!=. & private!=., statistics(n mean sd min max) f
> ormat(%9.4f)

    variable |         N      mean        sd       min       max
-------------+--------------------------------------------------
subsidy_as~r | 1516.0000    0.0029    0.0088    0.0000    0.2526
----------------------------------------------------------------

. 
. preserve

. duplicates drop gvn_turnover province year, force

Duplicates in terms of gvn_turnover province year

(1,703 observations deleted)

. tabstat gvn_turnover psec_turnover,  statistics(n mean sd min max) format(%9.2f)

   stats |  gvn_tu~r  psec_t~r
---------+--------------------
       N |    248.00    248.00
    mean |      0.23      0.24
      sd |      0.42      0.43
     min |      0.00      0.00
     max |      1.00      1.00
------------------------------

. restore

. 
. tabstat subsidy, by(private) statistics(n mean sd min max) format(%9.2f) 

Summary for variables: subsidy
     by categories of: private (Private firm=1, SOE=0)

 private |         N      mean        sd       min       max
---------+--------------------------------------------------
       0 |    920.00   4782.28  12763.39      0.00 161179.58
       1 |    596.00    465.21    628.42      0.00   4596.67
---------+--------------------------------------------------
   Total |   1516.00   3085.07  10169.68      0.00 161179.58
------------------------------------------------------------

. tabstat TotalAssets if subsidy!=., by(private) statistics(n mean sd min max) format(%9.2f
> )

Summary for variables: TotalAssets
     by categories of: private (Private firm=1, SOE=0)

 private |         N      mean        sd       min       max
---------+--------------------------------------------------
       0 |    920.00  4.21e+06  1.10e+07   9507.18  1.07e+08
       1 |    596.00 304726.02 482218.71   1068.88  7.62e+06
---------+--------------------------------------------------
   Total |   1516.00  2.68e+06  8.79e+06   1068.88  1.07e+08
------------------------------------------------------------

. tabstat subsidy_assets_number if subsidy!=., by(private) statistics(n mean sd min max) fo
> rmat(%9.4f)

Summary for variables: subsidy_assets_number
     by categories of: private (Private firm=1, SOE=0)

 private |         N      mean        sd       min       max
---------+--------------------------------------------------
       0 |  920.0000    0.0023    0.0055    0.0000    0.1005
       1 |  596.0000    0.0037    0.0121    0.0000    0.2526
---------+--------------------------------------------------
   Total | 1516.0000    0.0029    0.0088    0.0000    0.2526
------------------------------------------------------------

. tabstat revenue if subsidy!=.,  by(private) statistics(n mean sd min max) format(%9.2f)

Summary for variables: revenue
     by categories of: private (Private firm=1, SOE=0)

 private |         N      mean        sd       min       max
---------+--------------------------------------------------
       0 |    920.00  1.33e+06  2.67e+06   2027.81  1.04e+07
       1 |    595.00 191852.02 378385.85   2027.81  6.08e+06
---------+--------------------------------------------------
   Total |   1515.00 880659.25  2.17e+06   2027.81  1.04e+07
------------------------------------------------------------

. tabstat ROA if subsidy!=.,  by(private) statistics(n mean sd min max) format(%9.2f)

Summary for variables: ROA
     by categories of: private (Private firm=1, SOE=0)

 private |         N      mean        sd       min       max
---------+--------------------------------------------------
       0 |    920.00      5.36      9.22    -81.63    165.13
       1 |    596.00      8.16     11.96   -135.29     64.01
---------+--------------------------------------------------
   Total |   1516.00      6.46     10.47   -135.29    165.13
------------------------------------------------------------

. 
. ***********************
. *Main Results 
. ***********************
. *Table 2: Main effects
. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private, absorb(year provid industry_name_CS
> RC_f) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,355
Absorbing 3 HDFE groups                           F(   3,     30) =       4.72
Statistics robust to heteroskedasticity           Prob > F        =     0.0082
                                                  R-squared       =     0.1066
                                                  Adj R-squared   =     0.0780
                                                  Within R-sq.    =     0.0192
Number of clusters (provid)  =         31         Root MSE        =     0.4702

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0047786   .0267651     0.18   0.860     -.049883    .0594402
                       |
             1.private |    .175082   .0622639     2.81   0.009     .0479222    .3022418
                       |
L.gvn_turnover#private |
                  1 1  |  -.1000728   .0368562    -2.72   0.011    -.1753433   -.0248024
                       |
                 _cons |   .1998614   .0261537     7.64   0.000     .1464484    .2532744
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass1

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_revenue_w, absorb(year provid industry_name_CSRC_f) vc
> e(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,349
Absorbing 3 HDFE groups                           F(   4,     30) =       4.06
Statistics robust to heteroskedasticity           Prob > F        =     0.0095
                                                  R-squared       =     0.1238
                                                  Adj R-squared   =     0.0949
                                                  Within R-sq.    =     0.0379
Number of clusters (provid)  =         31         Root MSE        =     0.4447

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0106874   .0285247     0.37   0.711    -.0475678    .0689426
                       |
             1.private |   .0611768    .062767     0.97   0.338    -.0670105     .189364
                       |
L.gvn_turnover#private |
                  1 1  |   -.087702   .0377578    -2.32   0.027    -.1648137   -.0105904
                       |
         log_revenue_w |
                   L1. |  -.0497178    .017192    -2.89   0.007    -.0848285    -.014607
                       |
                 _cons |   .8325267   .2217912     3.75   0.001     .3795686    1.285485
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass2

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w, absorb(year provid industry_name_CSRC_f) vce
> (cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 3 HDFE groups                           F(   4,     30) =       5.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0030
                                                  R-squared       =     0.1335
                                                  Adj R-squared   =     0.1050
                                                  Within R-sq.    =     0.0494
Number of clusters (provid)  =         31         Root MSE        =     0.4421

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0105316    .027984     0.38   0.709    -.0466194    .0676826
                       |
             1.private |   .0258227   .0630552     0.41   0.685    -.1029533    .1545987
                       |
L.gvn_turnover#private |
                  1 1  |   -.085278    .038452    -2.22   0.034    -.1638076   -.0067485
                       |
          log_assets_w |
                   L1. |   -.064469   .0181224    -3.56   0.001    -.1014798   -.0274581
                       |
                 _cons |   1.076633   .2485929     4.33   0.000     .5689386    1.584327
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass3

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(provid industry_year) vce(clu
> ster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 2 HDFE groups                           F(   5,     30) =       7.31
Statistics robust to heteroskedasticity           Prob > F        =     0.0001
                                                  R-squared       =     0.1359
                                                  Adj R-squared   =     0.0984
                                                  Within R-sq.    =     0.0500
Number of clusters (provid)  =         31         Root MSE        =     0.4437

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0100913   .0278328     0.36   0.719    -.0467508    .0669334
                       |
             1.private |   .0314811    .058746     0.54   0.596    -.0884942    .1514564
                       |
L.gvn_turnover#private |
                  1 1  |  -.0857583   .0399145    -2.15   0.040    -.1672746   -.0042419
                       |
          log_assets_w |
                   L1. |  -.0650082   .0181234    -3.59   0.001    -.1020212   -.0279953
                       |
                 ROA_w |
                   L1. |  -.0012787    .004072    -0.31   0.756    -.0095948    .0070375
                       |
                 _cons |   1.090459   .2535095     4.30   0.000      .572724    1.608195
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass4

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(current_gvn_f industry_year) 
> vce(cluster provid)
(dropped 2 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =      1,348
Absorbing 2 HDFE groups                           F(   5,     30) =       7.18
Statistics robust to heteroskedasticity           Prob > F        =     0.0002
                                                  R-squared       =     0.1536
                                                  Adj R-squared   =     0.0908
                                                  Within R-sq.    =     0.0498
Number of clusters (provid)  =         31         Root MSE        =     0.4458

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |  -.0034326   .0285339    -0.12   0.905    -.0617066    .0548414
                       |
             1.private |   .0337462   .0603049     0.56   0.580    -.0894129    .1569052
                       |
L.gvn_turnover#private |
                  1 1  |  -.0849959   .0428838    -1.98   0.057    -.1725763    .0025846
                       |
          log_assets_w |
                   L1. |  -.0640672   .0185225    -3.46   0.002    -.1018952   -.0262391
                       |
                 ROA_w |
                   L1. |  -.0014464   .0042107    -0.34   0.734    -.0100458     .007153
                       |
                 _cons |   1.082401   .2611206     4.15   0.000     .5491221    1.615681
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        69           0          69     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass5

. 
. *outreg2 [gvn_lag1_subass1 gvn_lag1_subass2 gvn_lag1_subass3 gvn_lag1_subass4 gvn_lag1_subass5] using Table2.tex,
>  replace label dec(3)
. 
. *Figure 1: The turnover effect
. quietly reghdfe subsidy_assets_w i.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(current_gvn_f industry_
> year) vce(cluster provid)

. estimates store gvn_lag0

. 
. forval x=1/5{
  2. quietly reghdfe subsidy_assets_w  i.L`x'.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(current_gvn_f 
> industry_year) vce(cluster provid)
  3. estimates store gvn_lag`x' 
  4. }

. 
. forval x=1/2{
  2. quietly reghdfe subsidy_assets_w  i.F`x'.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(current_gvn_f 
> industry_year) vce(cluster provid)
  3. estimates store gvn_forward`x' 
  4. }

. 
. *outreg2 [gvn_forward2 gvn_forward1 gvn_lag0 gvn_lag1 gvn_lag2 gvn_lag3 gvn_lag4 gvn_lag5] using TableA8.tex, rep
> lace label dec(3)
. 
. coefplot gvn_forward2 gvn_forward1 gvn_lag0 gvn_lag1 gvn_lag2 gvn_lag3 gvn_lag4 gvn_lag5, /// 
>     keep(1F2.gvn_turnover#1.private 1F.gvn_turnover#1.private 1.gvn_turnover#1.private 1L.gvn_turnover#1.private 
> 1L2.gvn_turnover#1.private ///
>         1L3.gvn_turnover#1.private 1L4.gvn_turnover#1.private 1L5.gvn_turnover#1.private) /// 
>      yline(0, lp(dash))  vertical ///
>         coeflabels(1F2.gvn_turnover#1.private="-2" 1F.gvn_turnover#1.private="-1" 1.gvn_turnover#1.private = "0" 
> 1L.gvn_turnover#1.private="+1" ///
>         1L2.gvn_turnover#1.private="+2" 1L3.gvn_turnover#1.private="+3" ///
>         1L4.gvn_turnover#1.private="+4" 1L5.gvn_turnover#1.private="+5") /// 
>         xtitle("Years after governor turnover", size(small)) ///
>         levels(95 90) legend(order(1 "95%" 2 "90%") rows(1) position(6))  ciopts(lwidth(*1 *2) lcolor(gray black)
> ) msymbol(C) ///
>         scheme(lean1)  
(note:  named style C not found in class symbol, default attributes used)
(note:  named style C not found in class symbol, default attributes used)
(note:  named style C not found in class symbol, default attributes used)
(note:  named style C not found in class symbol, default attributes used)
(note:  named style C not found in class symbol, default attributes used)
(note:  named style C not found in class symbol, default attributes used)
(note:  named style C not found in class symbol, default attributes used)
(note:  named style C not found in class symbol, default attributes used)

. 
. *graph export Figure1.png, replace 
. 
. *Table 3 - Subsidy distribution: year 0-2 and 3 years or more after turnover
. preserve

. keep if L.gvn_turnover==1|L2.gvn_turnover==1|gvn_turnover==1|F.gvn_turnover==1 //observations from the year befor
> e turnover are kept because independent variables are lagged
(612 observations deleted)

. reghdfe subsidy_assets_w L.c.ROA_w##i.private L.log_assets_w, absorb(current_gvn_f industry_year) vce(cluster pro
> vid)
(dropped 2 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =        833
Absorbing 2 HDFE groups                           F(   4,     30) =       4.91
Statistics robust to heteroskedasticity           Prob > F        =     0.0036
                                                  R-squared       =     0.2407
                                                  Adj R-squared   =     0.1610
                                                  Within R-sq.    =     0.0916
Number of clusters (provid)  =         31         Root MSE        =     0.4310

                                    (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------
                 |               Robust
subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
           ROA_w |
             L1. |  -.0216412   .0091232    -2.37   0.024    -.0402733   -.0030091
                 |
       1.private |  -.2541973   .1051041    -2.42   0.022    -.4688486   -.0395461
                 |
private#cL.ROA_w |
              1  |   .0295249   .0093534     3.16   0.004     .0104227     .048627
                 |
    log_assets_w |
             L1. |  -.0554984   .0174872    -3.17   0.003    -.0912121   -.0197846
                 |
           _cons |    1.10741   .2708229     4.09   0.000     .5543159    1.660504
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        55          55           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto year012

. *outreg2 year012 using Table3.tex, replace  dec(3)
. restore

. 
. preserve

. drop if gvn_turnover==1 
(427 observations deleted)

. drop if L.gvn_turnover==1
(0 observations deleted)

. //drop if L2.gvn_turnover==1 //observations from two years after turnover are kept because independent variables 
> are lagged
. reghdfe subsidy_assets_w L.c.ROA_w##i.private L.log_assets_w, absorb(current_gvn_f industry_year) vce(cluster pro
> vid)
(dropped 2 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =        786
Absorbing 2 HDFE groups                           F(   4,     29) =      21.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2028
                                                  Adj R-squared   =     0.1223
                                                  Within R-sq.    =     0.0948
Number of clusters (provid)  =         30         Root MSE        =     0.4717

                                    (Std. Err. adjusted for 30 clusters in provid)
----------------------------------------------------------------------------------
                 |               Robust
subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
           ROA_w |
             L1. |  -.0189471   .0080842    -2.34   0.026    -.0354812   -.0024131
                 |
       1.private |  -.1590846   .1410653    -1.13   0.269    -.4475956    .1294264
                 |
private#cL.ROA_w |
              1  |   .0293695   .0113235     2.59   0.015     .0062103    .0525286
                 |
    log_assets_w |
             L1. |  -.0630485   .0203675    -3.10   0.004    -.1047046   -.0213923
                 |
           _cons |   1.164164   .3129347     3.72   0.001     .5241409    1.804187
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        49           0          49     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto year345

. *outreg2 year345 using Table3.tex, append  dec(3)
. restore

. 
. ***********************
. *Appendix
. ***********************
. *Figure A.1 - Total subsidies by year 
. graph bar (sum) subsidy, over(year) ytitle("Total subsidies") ///
> plotregion(fcolor(white)) graphregion(fcolor(white)) ytitle("Total subsidies (10,000 rmb)") 

. *graph export FigureA1.png, replace 
. 
. *Table A.2 - Number of firms by industry  
. preserve

. keep if year==2015
(1,707 observations deleted)

. tabout industry_name_CSRC private using TableA2.tex, style(tex) format(0) replace

Table output written to: TableA2.tex

 & \multicolumn{3}{c}{Private firm=1, SOE=0} \\
CSRC Industry Name
[Industry Level] Industries&0&1&Total \\
&No.&No.&No. \\
\hline
建筑业&36&54&90 \\
水利、环境和公共设施管理业&15&30&45 \\
电力、热力、燃气及水生产和供应业&76&19&95 \\
Total&127&103&230 \\

. restore

. count if private!=. //1845
  1,845

. /* note: industries in Chinese:
> construction: 建筑业
> Hydro, environment, and public facility mangagement: 水利、环境和公共设施管理业
> Electricity, thermo and water production and supply: 电力、热力、燃气及水生产和供应业
> */
. 
. *Figure A.4 
. preserve

. keep province current_gvn gvn_tenure

. duplicates drop

Duplicates in terms of all variables

(1,874 observations deleted)

. unique current_gvn
Number of unique values of current_gvn is  75
Number of records is  77

. tab gvn_tenure 

 gvn_tenure |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |          7        9.09        9.09
          2 |         14       18.18       27.27
          3 |         17       22.08       49.35
          4 |         10       12.99       62.34
          5 |          9       11.69       74.03
          6 |          7        9.09       83.12
          7 |          9       11.69       94.81
          8 |          1        1.30       96.10
          9 |          3        3.90      100.00
------------+-----------------------------------
      Total |         77      100.00

. su gvn_tenure, detail

                         gvn_tenure
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%            1              1
10%            2              1       Obs                  77
25%            2              1       Sum of Wgt.          77

50%            4                      Mean           4.038961
                        Largest       Std. Dev.      2.130243
75%            6              8
90%            7              9       Variance       4.537936
95%            8              9       Skewness       .5325184
99%            9              9       Kurtosis       2.411606

. hist gvn_tenure, discrete xtitle("Governor tenure (year)") xlabel(0(2)10) fcolor(ltblue) graphregion(color(white)
> ) bgcolor(white)  
(start=1, width=1)

. *graph export FigureA4.png, replace 
. restore

. 
. *Table A.3 - nonwinsorized results
. reghdfe subsidy_assets i.L.gvn_turnover##i.private, absorb(year provid industry_name_CSRC_f) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,355
Absorbing 3 HDFE groups                           F(   3,     30) =       2.45
Statistics robust to heteroskedasticity           Prob > F        =     0.0829
                                                  R-squared       =     0.0664
                                                  Adj R-squared   =     0.0365
                                                  Within R-sq.    =     0.0102
Number of clusters (provid)  =         31         Root MSE        =     0.8925

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
        subsidy_assets |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |  -.0045565   .0315462    -0.14   0.886    -.0689824    .0598694
                       |
             1.private |   .2377886    .098004     2.43   0.021     .0376377    .4379395
                       |
L.gvn_turnover#private |
                  1 1  |  -.1418057   .0655151    -2.16   0.039    -.2756053   -.0080061
                       |
                 _cons |   .2086277   .0375917     5.55   0.000     .1318552    .2854001
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass1

. reghdfe subsidy_assets i.L.gvn_turnover##i.private L.log_revenue, absorb(year provid industry_name_CSRC_f) vce(cl
> uster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,349
Absorbing 3 HDFE groups                           F(   4,     30) =       1.35
Statistics robust to heteroskedasticity           Prob > F        =     0.2737
                                                  R-squared       =     0.0838
                                                  Adj R-squared   =     0.0536
                                                  Within R-sq.    =     0.0277
Number of clusters (provid)  =         31         Root MSE        =     0.8663

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
        subsidy_assets |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0021308   .0348368     0.06   0.952    -.0690155     .073277
                       |
             1.private |   .0394635    .074311     0.53   0.599    -.1122999    .1912269
                       |
L.gvn_turnover#private |
                  1 1  |  -.1273424    .064883    -1.96   0.059    -.2598512    .0051665
                       |
           log_revenue |
                   L1. |   -.090987   .0533688    -1.70   0.099    -.1999807    .0180066
                       |
                 _cons |   1.367162   .6601215     2.07   0.047     .0190145     2.71531
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass2

. reghdfe subsidy_assets i.L.gvn_turnover##i.private L.log_assets, absorb(year provid industry_name_CSRC_f) vce(clu
> ster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 3 HDFE groups                           F(   4,     30) =       1.43
Statistics robust to heteroskedasticity           Prob > F        =     0.2475
                                                  R-squared       =     0.0829
                                                  Adj R-squared   =     0.0527
                                                  Within R-sq.    =     0.0282
Number of clusters (provid)  =         31         Root MSE        =     0.8664

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
        subsidy_assets |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0031003   .0339243     0.09   0.928    -.0661825     .072383
                       |
             1.private |   .0213195   .0742414     0.29   0.776    -.1303017    .1729407
                       |
L.gvn_turnover#private |
                  1 1  |  -.1226935   .0664132    -1.85   0.075    -.2583272    .0129403
                       |
            log_assets |
                   L1. |  -.0941117   .0431124    -2.18   0.037    -.1821589   -.0060645
                       |
                 _cons |    1.48896   .5673055     2.62   0.014     .3303678    2.647553
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass3

. reghdfe subsidy_assets i.L.gvn_turnover##i.private L.log_assets L.ROA, absorb(provid industry_year) vce(cluster p
> rovid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 2 HDFE groups                           F(   5,     30) =       1.90
Statistics robust to heteroskedasticity           Prob > F        =     0.1248
                                                  R-squared       =     0.0909
                                                  Adj R-squared   =     0.0516
                                                  Within R-sq.    =     0.0313
Number of clusters (provid)  =         31         Root MSE        =     0.8669

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
        subsidy_assets |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0064916   .0353502     0.18   0.856    -.0657032    .0786864
                       |
             1.private |   .0254799    .073698     0.35   0.732    -.1250315    .1759913
                       |
L.gvn_turnover#private |
                  1 1  |  -.1267933   .0585786    -2.16   0.039    -.2464269   -.0071598
                       |
            log_assets |
                   L1. |  -.0979945   .0448181    -2.19   0.037    -.1895253   -.0064637
                       |
                   ROA |
                   L1. |  -.0021703   .0016294    -1.33   0.193    -.0054981    .0011574
                       |
                 _cons |   1.552635   .5938004     2.61   0.014     .3399324    2.765337
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass4

. reghdfe subsidy_assets i.L.gvn_turnover##i.private L.log_assets L.ROA, absorb(current_gvn_f industry_year) vce(cl
> uster provid)
(dropped 2 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =      1,348
Absorbing 2 HDFE groups                           F(   5,     30) =       2.04
Statistics robust to heteroskedasticity           Prob > F        =     0.1009
                                                  R-squared       =     0.1073
                                                  Adj R-squared   =     0.0411
                                                  Within R-sq.    =     0.0308
Number of clusters (provid)  =         31         Root MSE        =     0.8723

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
        subsidy_assets |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |  -.0163821   .0409782    -0.40   0.692    -.1000708    .0673065
                       |
             1.private |   .0248241   .0748022     0.33   0.742    -.1279424    .1775907
                       |
L.gvn_turnover#private |
                  1 1  |   -.134052   .0723291    -1.85   0.074    -.2817678    .0136638
                       |
            log_assets |
                   L1. |  -.0961571   .0452265    -2.13   0.042    -.1885218   -.0037923
                       |
                   ROA |
                   L1. |  -.0021958   .0017084    -1.29   0.209    -.0056848    .0012932
                       |
                 _cons |   1.536416   .6036131     2.55   0.016     .3036737    2.769158
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        69           0          69     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass5

. 
. *unique current_gvn //75 
. *outreg2 [gvn_lag1_subass1 gvn_lag1_subass2 gvn_lag1_subass3 gvn_lag1_subass4 gvn_lag1_subass5] using TableA3.tex
> , replace label dec(3)
. 
. *Table A.4 - using log subsidy as Dv
. su log_subsidy_w

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
log_subsid~w |      1,605    5.592359    2.628635          0   10.41961

. reghdfe log_subsidy_w i.L.gvn_turnover##i.private, absorb(year provid industry_name_CSRC_f) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,355
Absorbing 3 HDFE groups                           F(   3,     30) =      14.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.2618
                                                  Adj R-squared   =     0.2382
                                                  Within R-sq.    =     0.0786
Number of clusters (provid)  =         31         Root MSE        =     2.1843

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
         log_subsidy_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .1535363    .131437     1.17   0.252    -.1148939    .4219665
                       |
             1.private |  -1.397781   .3818739    -3.66   0.001    -2.177671   -.6178902
                       |
L.gvn_turnover#private |
                  1 1  |  -.6462929   .1837684    -3.52   0.001    -1.021598   -.2709879
                       |
                 _cons |     6.3749   .1467094    43.45   0.000     6.075279    6.674521
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_logsub1

. reghdfe log_subsidy_w i.L.gvn_turnover##i.private L.log_revenue_w, absorb(year provid industry_name_CSRC_f) vce(c
> luster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,349
Absorbing 3 HDFE groups                           F(   4,     30) =      42.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4478
                                                  Adj R-squared   =     0.4296
                                                  Within R-sq.    =     0.3101
Number of clusters (provid)  =         31         Root MSE        =     1.8932

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
         log_subsidy_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .1460933   .1178657     1.24   0.225    -.0946207    .3868073
                       |
             1.private |   .0658463   .2345691     0.28   0.781    -.4132077    .5449003
                       |
L.gvn_turnover#private |
                  1 1  |  -.5389307   .1486157    -3.63   0.001    -.8424445   -.2354168
                       |
         log_revenue_w |
                   L1. |   .8053536   .0885136     9.10   0.000     .6245847    .9861225
                       |
                 _cons |  -3.860955   1.114143    -3.47   0.002    -6.136339   -1.585571
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_logsub2

. reghdfe log_subsidy_w i.L.gvn_turnover##i.private L.log_assets_w, absorb(year provid industry_name_CSRC_f) vce(cl
> uster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 3 HDFE groups                           F(   4,     30) =      29.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4210
                                                  Adj R-squared   =     0.4019
                                                  Within R-sq.    =     0.2768
Number of clusters (provid)  =         31         Root MSE        =     1.9380

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
         log_subsidy_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .1637856   .1192616     1.37   0.180    -.0797792    .4073503
                       |
             1.private |   .1566727   .2608431     0.60   0.553    -.3760399    .6893853
                       |
L.gvn_turnover#private |
                  1 1  |  -.6055884   .1563231    -3.87   0.001    -.9248428    -.286334
                       |
          log_assets_w |
                   L1. |   .7880145   .0972884     8.10   0.000     .5893251     .986704
                       |
                 _cons |  -4.345343   1.303063    -3.33   0.002    -7.006553   -1.684133
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_logsub3

. reghdfe log_subsidy_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(provid industry_year) vce(cluste
> r provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 2 HDFE groups                           F(   5,     30) =      31.58
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4233
                                                  Adj R-squared   =     0.3983
                                                  Within R-sq.    =     0.2768
Number of clusters (provid)  =         31         Root MSE        =     1.9438

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
         log_subsidy_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .1817213   .1217969     1.49   0.146    -.0670212    .4304637
                       |
             1.private |   .1423386   .2686222     0.53   0.600     -.406261    .6909383
                       |
L.gvn_turnover#private |
                  1 1  |   -.619906   .1623237    -3.82   0.001    -.9514153   -.2883968
                       |
          log_assets_w |
                   L1. |   .7886273   .0931652     8.46   0.000     .5983586     .978896
                       |
                 ROA_w |
                   L1. |   .0042967   .0145171     0.30   0.769    -.0253513    .0339446
                       |
                 _cons |  -4.380726    1.21154    -3.62   0.001    -6.855022    -1.90643
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_logsub4

. reghdfe log_subsidy_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(current_gvn_f industry_year) vce
> (cluster provid)
(dropped 2 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =      1,348
Absorbing 2 HDFE groups                           F(   5,     30) =      28.30
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4424
                                                  Adj R-squared   =     0.4010
                                                  Within R-sq.    =     0.2829
Number of clusters (provid)  =         31         Root MSE        =     1.9366

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
         log_subsidy_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .1218367   .1170873     1.04   0.306    -.1172874    .3609608
                       |
             1.private |   .1653246   .2751028     0.60   0.552    -.3965103    .7271596
                       |
L.gvn_turnover#private |
                  1 1  |   -.582254   .1642774    -3.54   0.001    -.9177533   -.2467547
                       |
          log_assets_w |
                   L1. |   .7925257   .0957116     8.28   0.000     .5970565    .9879949
                       |
                 ROA_w |
                   L1. |   .0027275   .0156341     0.17   0.863    -.0292017    .0346567
                       |
                 _cons |  -4.412964   1.240849    -3.56   0.001    -6.947116   -1.878812
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        69           0          69     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_logsub6

. 
. *outreg2 [gvn_lag1_logsub1 gvn_lag1_logsub2 gvn_lag1_logsub3 gvn_lag1_logsub4 gvn_lag1_logsub6] using TableA4.tex
> , replace label dec(3)
. 
. 
. *Table A.5 - additional firm characteristics: tax rate 
. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.tax_rate_income, absorb(provid industry_yea
> r) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,267
Absorbing 2 HDFE groups                           F(   5,     30) =       4.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0029
                                                  R-squared       =     0.1218
                                                  Adj R-squared   =     0.0812
                                                  Within R-sq.    =     0.0499
Number of clusters (provid)  =         31         Root MSE        =     0.4383

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0196528   .0295844     0.66   0.512    -.0407665    .0800721
                       |
             1.private |  -.0027269   .0614703    -0.04   0.965    -.1282661    .1228123
                       |
L.gvn_turnover#private |
                  1 1  |  -.0848865   .0433787    -1.96   0.060    -.1734777    .0037046
                       |
          log_assets_w |
                   L1. |  -.0625929   .0181637    -3.45   0.002    -.0996883   -.0254976
                       |
       tax_rate_income |
                   L1. |  -.0065068   .0046285    -1.41   0.170    -.0159594    .0029458
                       |
                 _cons |   1.192869   .2596776     4.59   0.000     .6625366    1.723201
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass4

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.tax_rate_income, absorb(current_gvn_f indus
> try_year) vce(cluster provid)
(dropped 1 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =      1,266
Absorbing 2 HDFE groups                           F(   5,     30) =       4.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0036
                                                  R-squared       =     0.1415
                                                  Adj R-squared   =     0.0734
                                                  Within R-sq.    =     0.0498
Number of clusters (provid)  =         31         Root MSE        =     0.4403

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0063876   .0292126     0.22   0.828    -.0532724    .0660476
                       |
             1.private |  -.0060157   .0637178    -0.09   0.925    -.1361448    .1241134
                       |
L.gvn_turnover#private |
                  1 1  |  -.0810328   .0458926    -1.77   0.088    -.1747579    .0126924
                       |
          log_assets_w |
                   L1. |  -.0618103   .0184968    -3.34   0.002    -.0995857   -.0240349
                       |
       tax_rate_income |
                   L1. |  -.0068774   .0047708    -1.44   0.160    -.0166208    .0028659
                       |
                 _cons |   1.194879   .2671276     4.47   0.000     .6493319    1.740427
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        69           0          69     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass5

. 
. *outreg2 [gvn_lag1_logsub4 gvn_lag1_logsub6] using TableA5.tex, replace label dec(3)
. 
. 
. *Table A.6 - additional firm characteristics
. ** adding other firm level indicators 
. su staff //1701 obs

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       staff |      1,701    7528.145    30565.36         11     294761

. gen lstaff=log(staff)
(250 missing values generated)

. su 成立year 

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
    成立year |      1,951    1996.461    6.185543       1950       2011

. gen firm_age=year-成立year 

. su firm_age

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
    firm_age |      1,951    15.03998    6.597314         -3         65

. 
. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.lstaff L.firm_age, absorb(year provid industry_name_CSRC_f
> ) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,320
Absorbing 3 HDFE groups                           F(   5,     30) =       3.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0257
                                                  R-squared       =     0.0978
                                                  Adj R-squared   =     0.0667
                                                  Within R-sq.    =     0.0165
Number of clusters (provid)  =         31         Root MSE        =     0.4461

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |     .01627   .0276154     0.59   0.560    -.0401282    .0726683
                       |
             1.private |   .1301372   .0597236     2.18   0.037     .0081652    .2521091
                       |
L.gvn_turnover#private |
                  1 1  |  -.0955105   .0386102    -2.47   0.019     -.174363   -.0166579
                       |
                lstaff |
                   L1. |  -.0115501   .0113442    -1.02   0.317     -.034718    .0116179
                       |
              firm_age |
                   L1. |  -.0033714   .0036668    -0.92   0.365    -.0108599    .0041171
                       |
                 _cons |   .3408166    .121964     2.79   0.009     .0917328    .5899004
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass1

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_revenue_w L.lstaff L.firm_age, absorb(year provid indu
> stry_name_CSRC_f) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,318
Absorbing 3 HDFE groups                           F(   6,     30) =       7.69
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1328
                                                  Adj R-squared   =     0.1022
                                                  Within R-sq.    =     0.0538
Number of clusters (provid)  =         31         Root MSE        =     0.4378

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0117516   .0305281     0.38   0.703     -.050595    .0740983
                       |
             1.private |   .0681352   .0571696     1.19   0.243    -.0486207    .1848911
                       |
L.gvn_turnover#private |
                  1 1  |  -.0975117    .038893    -2.51   0.018    -.1769417   -.0180816
                       |
         log_revenue_w |
                   L1. |  -.0975284   .0174711    -5.58   0.000    -.1332092   -.0618476
                       |
                lstaff |
                   L1. |   .0629829   .0142217     4.43   0.000     .0339382    .0920275
                       |
              firm_age |
                   L1. |  -.0035644   .0046446    -0.77   0.449    -.0130498    .0059211
                       |
                 _cons |   .9971817   .2140775     4.66   0.000     .5599772    1.434386
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass2

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.lstaff L.firm_age, absorb(year provid indus
> try_name_CSRC_f) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,319
Absorbing 3 HDFE groups                           F(   6,     30) =      14.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1484
                                                  Adj R-squared   =     0.1183
                                                  Within R-sq.    =     0.0716
Number of clusters (provid)  =         31         Root MSE        =     0.4337

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |    .010953    .029396     0.37   0.712    -.0490817    .0709877
                       |
             1.private |    .026742   .0541594     0.49   0.625    -.0838663    .1373504
                       |
L.gvn_turnover#private |
                  1 1  |  -.0860682   .0410221    -2.10   0.044    -.1698465   -.0022899
                       |
          log_assets_w |
                   L1. |  -.1181423   .0144304    -8.19   0.000    -.1476132   -.0886715
                       |
                lstaff |
                   L1. |   .0700232   .0139007     5.04   0.000     .0416343    .0984122
                       |
              firm_age |
                   L1. |   -.002991   .0041477    -0.72   0.476    -.0114618    .0054797
                       |
                 _cons |   1.299496   .2108676     6.16   0.000     .8688474    1.730145
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        31          31           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass3

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w L.lstaff L.firm_age, absorb(provid in
> dustry_year) vce(cluster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,319
Absorbing 2 HDFE groups                           F(   7,     30) =      13.07
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1509
                                                  Adj R-squared   =     0.1118
                                                  Within R-sq.    =     0.0725
Number of clusters (provid)  =         31         Root MSE        =     0.4353

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0115129   .0296797     0.39   0.701    -.0491011     .072127
                       |
             1.private |   .0330179    .050339     0.66   0.517    -.0697881    .1358238
                       |
L.gvn_turnover#private |
                  1 1  |  -.0864202   .0409943    -2.11   0.043    -.1701418   -.0026986
                       |
          log_assets_w |
                   L1. |  -.1188033   .0148124    -8.02   0.000    -.1490543   -.0885523
                       |
                 ROA_w |
                   L1. |  -.0017664   .0037479    -0.47   0.641    -.0094207    .0058879
                       |
                lstaff |
                   L1. |   .0698065   .0137401     5.08   0.000     .0417456    .0978675
                       |
              firm_age |
                   L1. |  -.0031816   .0042792    -0.74   0.463     -.011921    .0055578
                       |
                 _cons |   1.322116    .227608     5.81   0.000     .8572783    1.786954
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass4

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w L.lstaff L.firm_age, absorb(current_g
> vn_f industry_year) vce(cluster provid)
(dropped 2 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =      1,317
Absorbing 2 HDFE groups                           F(   7,     30) =      12.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1652
                                                  Adj R-squared   =     0.1002
                                                  Within R-sq.    =     0.0723
Number of clusters (provid)  =         31         Root MSE        =     0.4384

                                          (Std. Err. adjusted for 31 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |  -.0005543   .0318793    -0.02   0.986    -.0656605     .064552
                       |
             1.private |   .0344474   .0519696     0.66   0.512    -.0716886    .1405834
                       |
L.gvn_turnover#private |
                  1 1  |  -.0854415   .0446462    -1.91   0.065    -.1766211    .0057381
                       |
          log_assets_w |
                   L1. |  -.1183134   .0153021    -7.73   0.000    -.1495644   -.0870624
                       |
                 ROA_w |
                   L1. |  -.0018428   .0039623    -0.47   0.645     -.009935    .0062494
                       |
                lstaff |
                   L1. |   .0700401   .0141702     4.94   0.000     .0411006    .0989796
                       |
              firm_age |
                   L1. |  -.0029801   .0043798    -0.68   0.501    -.0119248    .0059647
                       |
                 _cons |   1.314331    .235544     5.58   0.000      .833286    1.795376
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        69           0          69     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass5

. 
. *outreg2 [gvn_lag1_subass1 gvn_lag1_subass2 gvn_lag1_subass3 gvn_lag1_subass4 gvn_lag1_subass5] using TableA6.tex
> , replace label dec(3)
. 
. 
. *Table A.7 - effect of firm subsidies on governor turnover
. reghdfe gvn_turnover c.L.subsidy_assets_w##i.private L.log_assets_w L.ROA_w, absorb(current_gvn_f industry_year) 
> vce(cluster provid)
(dropped 1 singleton observations)
(MWFE estimator converged in 10 iterations)

HDFE Linear regression                            Number of obs   =      1,282
Absorbing 2 HDFE groups                           F(   5,     30) =       0.30
Statistics robust to heteroskedasticity           Prob > F        =     0.9063
                                                  R-squared       =     0.5890
                                                  Adj R-squared   =     0.5568
                                                  Within R-sq.    =     0.0013
Number of clusters (provid)  =         31         Root MSE        =     0.2606

                                               (Std. Err. adjusted for 31 clusters in provid)
---------------------------------------------------------------------------------------------
                            |               Robust
               gvn_turnover |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------------+----------------------------------------------------------------
           subsidy_assets_w |
                        L1. |  -.0261698   .0231828    -1.13   0.268    -.0735154    .0211758
                            |
                  1.private |  -.0017166   .0109431    -0.16   0.876    -.0240655    .0206323
                            |
private#cL.subsidy_assets_w |
                         1  |   .0212976   .0334836     0.64   0.530     -.047085    .0896803
                            |
               log_assets_w |
                        L1. |  -.0000378   .0020672    -0.02   0.986    -.0042596    .0041841
                            |
                      ROA_w |
                        L1. |  -.0000232   .0011966    -0.02   0.985     -.002467    .0024207
                            |
                      _cons |    .194493   .0335966     5.79   0.000     .1258796    .2631064
---------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        69           0          69     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto m1

. *outreg2 m1 using TableA7.tex, replace dec(3)
. 
. 
. *Table A.8 - Tables underlying figure 1
. *codes in Figure 1 above
. 
. 
. *Table A.9 - Analysis by governor tenure length
. *Subset to only governors who have tenure periods longer than 2 years
. preserve

. tab gvn_tenure

 gvn_tenure |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |         44        2.26        2.26
          2 |        121        6.20        8.46
          3 |        449       23.01       31.47
          4 |        273       13.99       45.46
          5 |        373       19.12       64.58
          6 |        188        9.64       74.22
          7 |        172        8.82       83.03
          8 |         24        1.23       84.26
          9 |        307       15.74      100.00
------------+-----------------------------------
      Total |      1,951      100.00

. keep if gvn_tenure>2
(165 observations deleted)

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private, absorb(year provid industry_name_CSRC_f) vce(cluster provid
> )
(dropped 1 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      1,182
Absorbing 3 HDFE groups                           F(   3,     29) =       5.12
Statistics robust to heteroskedasticity           Prob > F        =     0.0058
                                                  R-squared       =     0.0981
                                                  Adj R-squared   =     0.0657
                                                  Within R-sq.    =     0.0211
Number of clusters (provid)  =         30         Root MSE        =     0.4822

                                          (Std. Err. adjusted for 30 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0055612   .0326828     0.17   0.866    -.0612826     .072405
                       |
             1.private |   .1871153   .0581423     3.22   0.003      .068201    .3060296
                       |
L.gvn_turnover#private |
                  1 1  |   -.090608    .039569    -2.29   0.029    -.1715357   -.0096804
                       |
                 _cons |   .1936977   .0252305     7.68   0.000     .1420955    .2452999
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        30          30           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass1

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_revenue_w, absorb(year provid industry_name_CSRC_f) vc
> e(cluster provid)
(dropped 1 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      1,176
Absorbing 3 HDFE groups                           F(   4,     29) =       4.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0062
                                                  R-squared       =     0.1130
                                                  Adj R-squared   =     0.0801
                                                  Within R-sq.    =     0.0372
Number of clusters (provid)  =         30         Root MSE        =     0.4543

                                          (Std. Err. adjusted for 30 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0188079   .0345151     0.54   0.590    -.0517835    .0893993
                       |
             1.private |   .0695272   .0640274     1.09   0.286    -.0614236     .200478
                       |
L.gvn_turnover#private |
                  1 1  |  -.0816108   .0409984    -1.99   0.056    -.1654619    .0022403
                       |
         log_revenue_w |
                   L1. |  -.0471325   .0181862    -2.59   0.015    -.0843275   -.0099376
                       |
                 _cons |   .7959605   .2369905     3.36   0.002     .3112606     1.28066
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        30          30           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass2

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w, absorb(year provid industry_name_CSRC_f) vce
> (cluster provid)
(dropped 1 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      1,177
Absorbing 3 HDFE groups                           F(   4,     29) =       5.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0016
                                                  R-squared       =     0.1191
                                                  Adj R-squared   =     0.0864
                                                  Within R-sq.    =     0.0451
Number of clusters (provid)  =         30         Root MSE        =     0.4527

                                          (Std. Err. adjusted for 30 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0207634   .0340032     0.61   0.546    -.0487809    .0903077
                       |
             1.private |   .0390609   .0654181     0.60   0.555    -.0947342    .1728559
                       |
L.gvn_turnover#private |
                  1 1  |  -.0839304   .0425717    -1.97   0.058    -.1709993    .0031386
                       |
          log_assets_w |
                   L1. |  -.0586106   .0181022    -3.24   0.003    -.0956338   -.0215874
                       |
                 _cons |   .9943194   .2519305     3.95   0.000     .4790637    1.509575
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
               provid |        30          30           0    *|
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass3

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(provid industry_year) vce(clu
> ster provid)
(dropped 1 singleton observations)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =      1,177
Absorbing 2 HDFE groups                           F(   5,     29) =      10.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1227
                                                  Adj R-squared   =     0.0797
                                                  Within R-sq.    =     0.0466
Number of clusters (provid)  =         30         Root MSE        =     0.4543

                                          (Std. Err. adjusted for 30 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |   .0219217   .0337605     0.65   0.521    -.0471263    .0909696
                       |
             1.private |   .0494251   .0609057     0.81   0.424     -.075141    .1739912
                       |
L.gvn_turnover#private |
                  1 1  |  -.0862918   .0450029    -1.92   0.065     -.178333    .0057494
                       |
          log_assets_w |
                   L1. |  -.0595629   .0184929    -3.22   0.003    -.0973853   -.0217406
                       |
                 ROA_w |
                   L1. |  -.0022182   .0037552    -0.59   0.559    -.0098984     .005462
                       |
                 _cons |   1.018256    .262026     3.89   0.001     .4823525    1.554159
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        30          30           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass4

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private L.log_assets_w L.ROA_w, absorb(current_gvn_f industry_year) 
> vce(cluster provid)
(dropped 1 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =      1,177
Absorbing 2 HDFE groups                           F(   5,     29) =       9.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1324
                                                  Adj R-squared   =     0.0741
                                                  Within R-sq.    =     0.0467
Number of clusters (provid)  =         30         Root MSE        =     0.4557

                                          (Std. Err. adjusted for 30 clusters in provid)
----------------------------------------------------------------------------------------
                       |               Robust
      subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
        L.gvn_turnover |
                    1  |  -.0024983   .0368893    -0.07   0.946    -.0779454    .0729488
                       |
             1.private |    .051539   .0624374     0.83   0.416    -.0761598    .1792379
                       |
L.gvn_turnover#private |
                  1 1  |  -.0749647   .0479808    -1.56   0.129    -.1730965     .023167
                       |
          log_assets_w |
                   L1. |  -.0585922   .0189233    -3.10   0.004    -.0972947   -.0198897
                       |
                 ROA_w |
                   L1. |  -.0021131   .0039509    -0.53   0.597    -.0101936    .0059674
                       |
                 _cons |   1.008416   .2693477     3.74   0.001     .4575376    1.559294
----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        50           0          50     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass5

. *outreg2 [gvn_lag1_subass1 gvn_lag1_subass2 gvn_lag1_subass3 gvn_lag1_subass4 gvn_lag1_subass5] using TableA9.tex
> , replace label dec(3)
. restore

. 
. 
. *Figure A.5 - sensitivity analysis
. gen treatment=L.gvn_turnover*private
(340 missing values generated)

. sensemakr subsidy_assets_w i.L.gvn_turnover i.private treatment L.log_assets_w L.ROA_w ///
> i.current_gvn_f i.provid i.industry_year, ///
> treat(treatment) benchmark(L.log_assets_w) contourplot kd(2 4 6 8 10) 

                                                            DOF    =    1253 
                                                            q      =    1.00 
                                                            alpha  =    0.05 
                                                            reduce =    TRUE
                                                            H0     =       0

 Treatment      |     Coef.      S.E.      t(H0)    R2yd.x     RV_q    RV_qa
----------------+-----------------------------------------------------------
      treatment |   -0.0876    0.0611    -1.4346    0.0016   0.0397        .

 Partial R2 of the treatment with the outcome (R2yd.x): 
 An extreme confounder (orthogonal to the covariates) that explains 100 percent of the 
 residual variance of the outcome, would need to explain at least 0.16 percent of the 
 residual variance of the treatment to fully account for the observed estimated effect. 
 
 Robustness Value, q = 1.00 (RV_q): 
 Unobserved confounders (orthogonal to the covariates) that explain more than 3.97 percent 
 of the residual variance of both the treatment and the outcome are strong enough to bring 
 the point estimate to 0 (a bias of 100 percent of the original estimate). Conversely, 
 unobserved confounders that do not explain more than 3.97 percent of the residual variance 
 of both the treatment and the outcome are not strong enough to bring the point estimate 
 to 0. 
 
 Robustness Value, q = 1.00, alpha = 0.05 (RV_qa): 
 Unobserved confounders (orthogonal to the covariates) that explain more than    . percent 
 of the residual variance of both the treatment and the outcome are strong enough to bring 
 the estimate to a range where it is no longer 'statistically different' from 0 (a bias 
 of 100 percent of the original estimate), at the significance level of alpha = 0.05. Conversely,
 unobserved confounders that do not explain more than    . percent of the residual variance 
 of both the treatment and the outcome are not strong enough to bring the estimate to a 
 range where it is no longer 'statistically different' from 0, at the significance 
 level of alpha = 0.05 
 
 Bounds on Omitted Variable Bias: 
 The table shows the maximum strength of unobserved confounders, bounded by a multiple of the 
 observed explanatory power of the chosen benchmark covariate(s) with the treatment and the outcome.

 Bound                 |   R2dz.x   R2yz.dx     Coef.      S.E.     t(H0)  Lower CI Upper CI 
-----------------------+----------------------------------------------------------------------
 2.00x  L.log_assets_w |   0.0001    0.0682   -0.0823    0.0590   -1.3953   -0.1980   0.0334 
 4.00x  L.log_assets_w |   0.0002    0.1363   -0.0770    0.0568   -1.3557   -0.1884   0.0344 
 6.00x  L.log_assets_w |   0.0003    0.2045   -0.0717    0.0545   -1.3149   -0.1786   0.0353 
 8.00x  L.log_assets_w |   0.0004    0.2726   -0.0664    0.0521   -1.2731   -0.1686   0.0359 
10.00x  L.log_assets_w |   0.0004    0.3408   -0.0610    0.0496   -1.2300   -0.1584   0.0363 


 Extreme Bound         |   R2dz.x   R2yz.dx     Coef.
-----------------------+------------------------------ 
 2.00x  L_log_assets_w |   0.0001    1.0000   -0.0673 
 4.00x  L_log_assets_w |   0.0002    1.0000   -0.0588 
 6.00x  L_log_assets_w |   0.0003    1.0000   -0.0523 
 8.00x  L_log_assets_w |   0.0004    1.0000   -0.0469 
10.00x  L_log_assets_w |   0.0004    1.0000   -0.0421 

. 
. *graph export FigureA5.png, replace 
. 
. 
. *Table A.11 - results for provincial party secretary/mayor/city party secretary 
. reghdfe subsidy_assets_w i.L.psec_turnover##i.private L.log_assets_w L.ROA_w, absorb(provid industry_year) vce(cl
> uster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 2 HDFE groups                           F(   5,     30) =       7.92
Statistics robust to heteroskedasticity           Prob > F        =     0.0001
                                                  R-squared       =     0.1345
                                                  Adj R-squared   =     0.0970
                                                  Within R-sq.    =     0.0485
Number of clusters (provid)  =         31         Root MSE        =     0.4440

                                           (Std. Err. adjusted for 31 clusters in provid)
-----------------------------------------------------------------------------------------
                        |               Robust
       subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
        L.psec_turnover |
                     1  |   .0316736   .0318315     1.00   0.328     -.033335    .0966822
                        |
              1.private |     .01306   .0641893     0.20   0.840     -.118032    .1441521
                        |
L.psec_turnover#private |
                   1 1  |   -.007391   .0440102    -0.17   0.868    -.0972718    .0824898
                        |
           log_assets_w |
                    L1. |  -.0648913   .0182951    -3.55   0.001    -.1022549   -.0275276
                        |
                  ROA_w |
                    L1. |  -.0013099   .0040807    -0.32   0.750    -.0096437    .0070239
                        |
                  _cons |   1.083301   .2534297     4.27   0.000     .5657281    1.600873
-----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass1

. reghdfe subsidy_assets_w i.L.psec_turnover##i.private L.log_assets_w L.ROA_w, absorb(current_psec_f industry_year
> ) vce(cluster provid)
(dropped 1 singleton observations)
(MWFE estimator converged in 9 iterations)

HDFE Linear regression                            Number of obs   =      1,349
Absorbing 2 HDFE groups                           F(   5,     30) =       9.31
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1315
                                                  Adj R-squared   =     0.0768
                                                  Within R-sq.    =     0.0479
Number of clusters (provid)  =         31         Root MSE        =     0.4491

                                           (Std. Err. adjusted for 31 clusters in provid)
-----------------------------------------------------------------------------------------
                        |               Robust
       subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
        L.psec_turnover |
                     1  |    .048935   .0338016     1.45   0.158    -.0200971     .117967
                        |
              1.private |   .0119324    .058454     0.20   0.840    -.1074465    .1313114
                        |
L.psec_turnover#private |
                   1 1  |  -.0151966   .0441611    -0.34   0.733    -.1053856    .0749924
                        |
           log_assets_w |
                    L1. |  -.0625162   .0158992    -3.93   0.000    -.0949868   -.0300456
                        |
                  ROA_w |
                    L1. |   .0000893   .0043772     0.02   0.984    -.0088502    .0090289
                        |
                  _cons |   1.039934   .2215425     4.69   0.000     .5874841    1.492384
-----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------+
    Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------+---------------------------------------|
 current_psec_f |        56           0          56     |
  industry_year |        21           1          20     |
--------------------------------------------------------+

. est sto gvn_lag1_subass2

. reghdfe subsidy_assets_w i.L.mayor_turnover##i.private L.log_assets_w L.ROA_w, absorb(provid industry_year) vce(c
> luster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 2 HDFE groups                           F(   5,     30) =       9.40
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1342
                                                  Adj R-squared   =     0.0967
                                                  Within R-sq.    =     0.0481
Number of clusters (provid)  =         31         Root MSE        =     0.4441

                                            (Std. Err. adjusted for 31 clusters in provid)
------------------------------------------------------------------------------------------
                         |               Robust
        subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
        L.mayor_turnover |
                      1  |  -.0128127   .0283732    -0.45   0.655    -.0707584     .045133
                         |
               1.private |   .0118885   .0611963     0.19   0.847    -.1130911    .1368681
                         |
L.mayor_turnover#private |
                    1 1  |  -.0034426   .0435138    -0.08   0.937    -.0923097    .0854245
                         |
            log_assets_w |
                     L1. |  -.0648167   .0180722    -3.59   0.001     -.101725   -.0279084
                         |
                   ROA_w |
                     L1. |  -.0012798   .0041031    -0.31   0.757    -.0096595    .0070999
                         |
                   _cons |    1.09331   .2545956     4.29   0.000      .573356    1.613263
------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass3

. reghdfe subsidy_assets_w i.L.mayor_turnover##i.private L.log_assets_w L.ROA_w, absorb(mayor_f industry_year) vce(
> cluster provid)
(dropped 27 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =      1,323
Absorbing 2 HDFE groups                           F(   5,     30) =       5.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0008
                                                  R-squared       =     0.2100
                                                  Adj R-squared   =     0.0855
                                                  Within R-sq.    =     0.0466
Number of clusters (provid)  =         31         Root MSE        =     0.4411

                                            (Std. Err. adjusted for 31 clusters in provid)
------------------------------------------------------------------------------------------
                         |               Robust
        subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
        L.mayor_turnover |
                      1  |   .0071671   .0372995     0.19   0.849    -.0690087    .0833429
                         |
               1.private |   .0387715   .0779205     0.50   0.622    -.1203633    .1979063
                         |
L.mayor_turnover#private |
                    1 1  |  -.0121542   .0455464    -0.27   0.791    -.1051724    .0808639
                         |
            log_assets_w |
                     L1. |  -.0586568   .0200982    -2.92   0.007    -.0997027   -.0176108
                         |
                   ROA_w |
                     L1. |   -.002142   .0044056    -0.49   0.630    -.0111395    .0068555
                         |
                   _cons |   1.004986   .2881594     3.49   0.002     .4164856    1.593486
------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
       mayor_f |       156           0         156     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass4

. reghdfe subsidy_assets_w i.L.msec_turnover##i.private L.log_assets_w L.ROA_w, absorb(provid industry_year) vce(cl
> uster provid)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,350
Absorbing 2 HDFE groups                           F(   5,     30) =       9.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1358
                                                  Adj R-squared   =     0.0984
                                                  Within R-sq.    =     0.0499
Number of clusters (provid)  =         31         Root MSE        =     0.4437

                                           (Std. Err. adjusted for 31 clusters in provid)
-----------------------------------------------------------------------------------------
                        |               Robust
       subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
        L.msec_turnover |
                     1  |  -.0232182   .0242047    -0.96   0.345    -.0726507    .0262143
                        |
              1.private |   .0226185   .0627739     0.36   0.721    -.1055829    .1508199
                        |
L.msec_turnover#private |
                   1 1  |  -.0518965   .0484719    -1.07   0.293    -.1508893    .0470963
                        |
           log_assets_w |
                    L1. |  -.0646972   .0180875    -3.58   0.001    -.1016369   -.0277576
                        |
                  ROA_w |
                    L1. |  -.0012843   .0040865    -0.31   0.755      -.00963    .0070614
                        |
                  _cons |   1.093797   .2523571     4.33   0.000     .5784147    1.609179
-----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        provid |        31          31           0    *|
 industry_year |        21           0          21     |
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto gvn_lag1_subass5

. reghdfe subsidy_assets_w i.L.msec_turnover##i.private L.log_assets_w L.ROA_w, absorb(msec_f industry_year) vce(cl
> uster provid)
(dropped 23 singleton observations)
(MWFE estimator converged in 11 iterations)

HDFE Linear regression                            Number of obs   =      1,327
Absorbing 2 HDFE groups                           F(   5,     29) =       5.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0008
                                                  R-squared       =     0.2013
                                                  Adj R-squared   =     0.0823
                                                  Within R-sq.    =     0.0486
Number of clusters (provid)  =         30         Root MSE        =     0.4416

                                           (Std. Err. adjusted for 30 clusters in provid)
-----------------------------------------------------------------------------------------
                        |               Robust
       subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
        L.msec_turnover |
                     1  |   -.032679    .028286    -1.16   0.257    -.0905303    .0251723
                        |
              1.private |   .0628671   .0769747     0.82   0.421    -.0945638    .2202981
                        |
L.msec_turnover#private |
                   1 1  |  -.0438866   .0464877    -0.94   0.353    -.1389647    .0511915
                        |
           log_assets_w |
                    L1. |  -.0562339   .0198151    -2.84   0.008    -.0967603   -.0157075
                        |
                  ROA_w |
                    L1. |  -.0018741   .0044632    -0.42   0.678    -.0110025    .0072542
                        |
                  _cons |   .9742472   .2812374     3.46   0.002     .3990521    1.549442
-----------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
        msec_f |       148           0         148     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass5

. 
. *outreg2 [gvn_lag1_subass1 gvn_lag1_subass2 gvn_lag1_subass3 gvn_lag1_subass4 gvn_lag1_subass5 gvn_lag1_subass5] 
> using TableA11.tex, replace label dec(3)
. 
. 
. *Table A.14 - Triple interaction with governors near retirement
. gen gvn_age_num=real(gvn_age)
(3,121 missing values generated)

. drop if gvn_age=="NA"
(520 observations deleted)

. 
. *calculate governor starting age
. egen gvn_age_max = max(gvn_age_num), by(current_gvn province)
(2601 missing values generated)

. gen gvn_age_start=gvn_age_max-gvn_tenure 
(2,601 missing values generated)

. egen gvn_start=min(gvn_age_start>58), by(current_gvn province)

. tab gvn_start

  gvn_start |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |      1,263       31.32       31.32
          1 |      2,769       68.68      100.00
------------+-----------------------------------
      Total |      4,032      100.00

. unique current_gvn if gvn_start==1 //10
Number of unique values of current_gvn is  11
Number of records is  2769

. tab province if gvn_start==1 

            年份
   地区 |      Freq.     Percent        Cum.
-------------------------+-----------------------------------
                  云南省 |          3        1.79        1.79
                  安徽省 |         18       10.71       12.50
          广西壮族自治区 |         12        7.14       19.64
        新疆维吾尔自治区 |          6        3.57       23.21
                  江苏省 |         90       53.57       76.79
                  河南省 |          6        3.57       80.36
                  浙江省 |         18       10.71       91.07
                  海南省 |          1        0.60       91.67
                  贵州省 |          6        3.57       95.24
                  陕西省 |          8        4.76      100.00
-------------------------+-----------------------------------
                   Total |        168      100.00

. 
. *interaction model 
. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private##i.gvn_start, absorb(year industry_name_CSRC_f) vce(cluster 
> provid)
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =      1,003
Absorbing 2 HDFE groups                           F(   7,     26) =       2.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0682
                                                  R-squared       =     0.0397
                                                  Adj R-squared   =     0.0251
                                                  Within R-sq.    =     0.0169
Number of clusters (provid)  =         27         Root MSE        =     0.5120

                                                    (Std. Err. adjusted for 27 clusters in provid)
--------------------------------------------------------------------------------------------------
                                 |               Robust
                subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
                  L.gvn_turnover |
                              1  |   .0022968   .0424486     0.05   0.957    -.0849575    .0895511
                                 |
                       1.private |   .1343159   .0751845     1.79   0.086     -.020228    .2888598
                                 |
          L.gvn_turnover#private |
                            1 1  |  -.1334479    .050641    -2.64   0.014    -.2375419   -.0293539
                                 |
                     1.gvn_start |   .0126477   .0624952     0.20   0.841    -.1158131    .1411085
                                 |
        L.gvn_turnover#gvn_start |
                            1 1  |  -.0301111   .0601929    -0.50   0.621    -.1538393    .0936171
                                 |
               private#gvn_start |
                            1 1  |   .0655809   .0954338     0.69   0.498    -.1305861     .261748
                                 |
L.gvn_turnover#private#gvn_start |
                          1 1 1  |   .0493506    .097139     0.51   0.616    -.1503215    .2490227
                                 |
                           _cons |    .221463   .0419677     5.28   0.000     .1351972    .3077288
--------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+

. est sto gvn_lag1_subass1

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private##i.gvn_start L.log_revenue_w, absorb(year industry_name_CSRC
> _f) vce(cluster provid)
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =        998
Absorbing 2 HDFE groups                           F(   8,     26) =       1.30
Statistics robust to heteroskedasticity           Prob > F        =     0.2851
                                                  R-squared       =     0.0596
                                                  Adj R-squared   =     0.0443
                                                  Within R-sq.    =     0.0358
Number of clusters (provid)  =         27         Root MSE        =     0.4791

                                                    (Std. Err. adjusted for 27 clusters in provid)
--------------------------------------------------------------------------------------------------
                                 |               Robust
                subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
                  L.gvn_turnover |
                              1  |   .0133016   .0406587     0.33   0.746    -.0702735    .0968767
                                 |
                       1.private |    .036929    .067778     0.54   0.590    -.1023907    .1762487
                                 |
          L.gvn_turnover#private |
                            1 1  |  -.1043545   .0541878    -1.93   0.065     -.215739    .0070301
                                 |
                     1.gvn_start |    .005495   .0531083     0.10   0.918    -.1036707    .1146607
                                 |
        L.gvn_turnover#gvn_start |
                            1 1  |   -.050322   .0589805    -0.85   0.401    -.1715582    .0709142
                                 |
               private#gvn_start |
                            1 1  |   .0929627   .0888714     1.05   0.305    -.0897152    .2756405
                                 |
L.gvn_turnover#private#gvn_start |
                          1 1 1  |   .0180081    .101174     0.18   0.860    -.1899579    .2259742
                                 |
                   log_revenue_w |
                             L1. |  -.0560935   .0235898    -2.38   0.025     -.104583    -.007604
                                 |
                           _cons |    .905424   .2870585     3.15   0.004     .3153669    1.495481
--------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+

. est sto gvn_lag1_subass2

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private##i.gvn_start L.log_assets_w, absorb(year industry_name_CSRC_
> f) vce(cluster provid)
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =        999
Absorbing 2 HDFE groups                           F(   8,     26) =       3.39
Statistics robust to heteroskedasticity           Prob > F        =     0.0084
                                                  R-squared       =     0.0817
                                                  Adj R-squared   =     0.0667
                                                  Within R-sq.    =     0.0583
Number of clusters (provid)  =         27         Root MSE        =     0.4733

                                                    (Std. Err. adjusted for 27 clusters in provid)
--------------------------------------------------------------------------------------------------
                                 |               Robust
                subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
                  L.gvn_turnover |
                              1  |   .0138822   .0389914     0.36   0.725    -.0662657    .0940302
                                 |
                       1.private |  -.0099874    .062099    -0.16   0.873    -.1376337    .1176588
                                 |
          L.gvn_turnover#private |
                            1 1  |  -.0958126   .0536335    -1.79   0.086    -.2060579    .0144327
                                 |
                     1.gvn_start |  -.0068486   .0540529    -0.13   0.900     -.117956    .1042587
                                 |
        L.gvn_turnover#gvn_start |
                            1 1  |  -.0662539   .0617935    -1.07   0.293    -.1932723    .0607646
                                 |
               private#gvn_start |
                            1 1  |   .1084208   .0847613     1.28   0.212    -.0658086    .2826502
                                 |
L.gvn_turnover#private#gvn_start |
                          1 1 1  |   .0378546   .0943335     0.40   0.691    -.1560507      .23176
                                 |
                    log_assets_w |
                             L1. |  -.0882895   .0215152    -4.10   0.000    -.1325146   -.0440644
                                 |
                           _cons |   1.374494   .2737199     5.02   0.000     .8118545    1.937133
--------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
                 year |         7           0           7     |
 industry_name_CSRC_f |         3           1           2     |
--------------------------------------------------------------+

. est sto gvn_lag1_subass3

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private##i.gvn_start L.log_assets_w L.ROA_w, absorb(industry_year) v
> ce(cluster provid)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =        999
Absorbing 1 HDFE group                            F(   9,     26) =       2.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0154
                                                  R-squared       =     0.0879
                                                  Adj R-squared   =     0.0606
                                                  Within R-sq.    =     0.0590
Number of clusters (provid)  =         27         Root MSE        =     0.4748

                                                    (Std. Err. adjusted for 27 clusters in provid)
--------------------------------------------------------------------------------------------------
                                 |               Robust
                subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
                  L.gvn_turnover |
                              1  |   .0154938   .0385738     0.40   0.691    -.0637957    .0947834
                                 |
                       1.private |  -.0126142   .0487881    -0.26   0.798    -.1128997    .0876712
                                 |
          L.gvn_turnover#private |
                            1 1  |  -.0933544   .0520562    -1.79   0.085    -.2003574    .0136486
                                 |
                     1.gvn_start |  -.0078645   .0570546    -0.14   0.891    -.1251419    .1094129
                                 |
        L.gvn_turnover#gvn_start |
                            1 1  |  -.0710117   .0624596    -1.14   0.266    -.1993993    .0573759
                                 |
               private#gvn_start |
                            1 1  |   .1243811   .0799593     1.56   0.132    -.0399777    .2887399
                                 |
L.gvn_turnover#private#gvn_start |
                          1 1 1  |   .0461644   .0939404     0.49   0.627    -.1469329    .2392617
                                 |
                    log_assets_w |
                             L1. |  -.0880077   .0205049    -4.29   0.000    -.1301562   -.0458592
                                 |
                           ROA_w |
                             L1. |   .0002032   .0050746     0.04   0.968    -.0102278    .0106342
                                 |
                           _cons |   1.368866   .2580536     5.30   0.000     .8384288    1.899302
--------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 industry_year |        21           0          21     |
-------------------------------------------------------+

. est sto gvn_lag1_subass4

. reghdfe subsidy_assets_w i.L.gvn_turnover##i.private##i.gvn_start L.log_assets_w L.ROA_w, absorb(current_gvn_f in
> dustry_year) vce(cluster provid)
(dropped 2 singleton observations)
note: 1bn.gvn_start is probably collinear with the fixed effects (all partialled-out values are close to zero; tol 
> = 1.0e-09)
(MWFE estimator converged in 10 iterations)
note: 1.gvn_start omitted because of collinearity

HDFE Linear regression                            Number of obs   =        997
Absorbing 2 HDFE groups                           F(   8,     26) =       4.18
Statistics robust to heteroskedasticity           Prob > F        =     0.0025
                                                  R-squared       =     0.1849
                                                  Adj R-squared   =     0.1050
                                                  Within R-sq.    =     0.0624
Number of clusters (provid)  =         27         Root MSE        =     0.4638

                                                    (Std. Err. adjusted for 27 clusters in provid)
--------------------------------------------------------------------------------------------------
                                 |               Robust
                subsidy_assets_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
                  L.gvn_turnover |
                              1  |  -.0273083   .0386192    -0.71   0.486    -.1066913    .0520747
                                 |
                       1.private |   -.034877   .0597374    -0.58   0.564    -.1576691     .087915
                                 |
          L.gvn_turnover#private |
                            1 1  |  -.0923549   .0610709    -1.51   0.143     -.217888    .0331781
                                 |
                     1.gvn_start |          0  (omitted)
                                 |
        L.gvn_turnover#gvn_start |
                            1 1  |   .0260627   .0738741     0.35   0.727    -.1257876     .177913
                                 |
               private#gvn_start |
                            1 1  |    .184266   .1111537     1.66   0.109    -.0442137    .4127457
                                 |
L.gvn_turnover#private#gvn_start |
                          1 1 1  |   .0105315   .1072625     0.10   0.923    -.2099497    .2310126
                                 |
                    log_assets_w |
                             L1. |  -.0955951   .0191082    -5.00   0.000    -.1348726   -.0563176
                                 |
                           ROA_w |
                             L1. |  -.0009673    .005213    -0.19   0.854    -.0116827    .0097481
                                 |
                           _cons |   1.484155   .2443799     6.07   0.000     .9818246    1.986485
--------------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 current_gvn_f |        62           0          62     |
 industry_year |        21           1          20     |
-------------------------------------------------------+

. est sto gvn_lag1_subass5

. 
. *outreg2 [gvn_lag1_subass1 gvn_lag1_subass2 gvn_lag1_subass3 gvn_lag1_subass4 gvn_lag1_subass5] using TableA14.te
> x, replace label dec(3)
.  
.  
. *Fig A.6: distribution graphs on ROA for private and SOEs
. preserve

. collapse (mean) ROA_w, by(private industry_name_CSRC) 

. drop if private==.
(4 observations deleted)

. reshape wide ROA_w, i(industry) j(private)
(note: j = 0 1)

Data                               long   ->   wide
-----------------------------------------------------------------------------
Number of obs.                        6   ->       3
Number of variables                   3   ->       3
j variable (2 values)           private   ->   (dropped)
xij variables:
                                  ROA_w   ->   ROA_w0 ROA_w1
-----------------------------------------------------------------------------

. rename ROA_w0 ROA_w_SOE 

. rename ROA_w1 ROA_w_private

. graph bar ROA_w_private ROA_w_SOE, over(industry_name_CSRC, relabel(1 "Construction" 2 "Hydro, environment" 3 "El
> ectricity, thermo, gas")) ///
> legend(label(1 "Private enterprises") label (2 "State-owned enterprises")) ///
> bgcolor(white) graphregion(color(white)) nofill ///
> bar(1, color(black%50)) bar(2, color(black%30))

. *title("Average ROA for private firms and SOEs across industries")
. *note("") 
. *graph export "FigureA6.png", as(png) replace
. restore

. 
. 
. *Table A.15 - omparison of profit levels for private firms and SOEs
. preserve

. keep if L.gvn_turnover==1|L2.gvn_turnover==1|gvn_turnover==1|F.gvn_turnover==1
(3,064 observations deleted)

. reghdfe ROA_w i.private L.log_assets_w, absorb(provid industry_name_CSRC_f year) vce(cluster provid)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =        650
Absorbing 3 HDFE groups                           F(   2,     26) =      11.29
Statistics robust to heteroskedasticity           Prob > F        =     0.0003
                                                  R-squared       =     0.1508
                                                  Adj R-squared   =     0.0995
                                                  Within R-sq.    =     0.0476
Number of clusters (provid)  =         27         Root MSE        =     7.3217

                                (Std. Err. adjusted for 27 clusters in provid)
------------------------------------------------------------------------------
             |               Robust
       ROA_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   1.private |  -.2813784   .9832747    -0.29   0.777    -2.302529    1.739772
             |
log_assets_w |
         L1. |   -1.33535   .2823851    -4.73   0.000    -1.915801    -.754899
             |
       _cons |   23.87248   3.616132     6.60   0.000     16.43941    31.30554
------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
               provid |        27          27           0    *|
 industry_name_CSRC_f |         3           0           3     |
                 year |         7           1           6     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto est12

. *outreg2 est12 using TableA15.tex, replace label dec(3)
. restore

. 
. preserve

. drop if gvn_turnover==1 
(324 observations deleted)

. drop if L.gvn_turnover==1
(0 observations deleted)

. reghdfe ROA_w i.private L.log_assets_w, absorb(provid industry_name_CSRC_f year) vce(cluster provid)
(MWFE estimator converged in 8 iterations)

HDFE Linear regression                            Number of obs   =        599
Absorbing 3 HDFE groups                           F(   2,     26) =       5.54
Statistics robust to heteroskedasticity           Prob > F        =     0.0099
                                                  R-squared       =     0.1925
                                                  Adj R-squared   =     0.1392
                                                  Within R-sq.    =     0.0746
Number of clusters (provid)  =         27         Root MSE        =     6.7848

                                (Std. Err. adjusted for 27 clusters in provid)
------------------------------------------------------------------------------
             |               Robust
       ROA_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   1.private |  -.3243538   .6708002    -0.48   0.633    -1.703203    1.054496
             |
log_assets_w |
         L1. |  -1.539914   .4657522    -3.31   0.003    -2.497282   -.5825471
             |
       _cons |    26.7641   5.881943     4.55   0.000     14.67359    38.85461
------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
               provid |        27          27           0    *|
 industry_name_CSRC_f |         3           0           3     |
                 year |         7           1           6     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto est345

. *outreg2 year345 using TableA15.tex, append  dec(3)
. restore

. 
. *full sample
. reghdfe ROA_w i.private L.log_assets_w, absorb(provid industry_name_CSRC_f year) vce(cluster provid) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =      1,052
Absorbing 3 HDFE groups                           F(   2,     26) =       7.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0031
                                                  R-squared       =     0.1534
                                                  Adj R-squared   =     0.1226
                                                  Within R-sq.    =     0.0589
Number of clusters (provid)  =         27         Root MSE        =     7.0428

                                (Std. Err. adjusted for 27 clusters in provid)
------------------------------------------------------------------------------
             |               Robust
       ROA_w |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   1.private |  -.2448168   .7442044    -0.33   0.745    -1.774551    1.284917
             |
log_assets_w |
         L1. |  -1.435426    .376598    -3.81   0.001    -2.209534   -.6613179
             |
       _cons |   25.21398   4.736005     5.32   0.000     15.47898    34.94898
------------------------------------------------------------------------------

Absorbed degrees of freedom:
--------------------------------------------------------------+
          Absorbed FE | Categories  - Redundant  = Num. Coefs |
----------------------+---------------------------------------|
               provid |        27          27           0    *|
 industry_name_CSRC_f |         3           0           3     |
                 year |         7           1           6     |
--------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est sto est3

. *outreg2 est3 using TableA15.tex, append label dec(3)
. 
. log close
      name:  <unnamed>
       log:  C:\Users\Siyao\Dropbox\Yue-Siyao\Project Subsidy\PSRM replication files\analysis_main.log
  log type:  text
 closed on:  18 Aug 2022, 21:35:59
-------------------------------------------------------------------------------------------------------------------
